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from langchain.agents import create_csv_agent, AgentType | |
import utils | |
class CSVAgent: | |
def __init__(self, llm, embeddings, file): | |
self.llm = llm | |
self.file = file | |
self.summary_index_name = "canvas-discussions-summary" | |
self.folder_path = "vector_stores/" | |
self.summary_index_file = "vector_stores/canvas-discussions-summary.faiss" | |
self.summary_pickle_file = "vector_stores/canvas-discussions-summary.pkl" | |
self.summary_docs = utils.get_csv_files(self.file, source_column='student_name') | |
self.summary_index = self.get_search_index(embeddings) | |
self.agent = self.create_agent() | |
def get_search_index(self, embeddings): | |
if utils.index_exists(self.summary_pickle_file, self.summary_index_file): | |
# Load index from pickle file | |
search_index = utils.load_index(self.folder_path, self.summary_index_name, embeddings) | |
else: | |
search_index = utils.create_index(self.folder_path, self.summary_index_name, embeddings, self.summary_docs) | |
print("Created index") | |
return search_index | |
def create_agent(self): | |
agent = create_csv_agent( | |
self.llm, | |
self.file, | |
verbose=True, | |
agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION, | |
) | |
return agent | |